Sentence examples for matrix can achieve from inspiring English sources

It is obvious that the adaptive sparsifying matrix can achieve better reconstruction performance for voiced speech than the DCT basis with u s  ≤ 0.5.

Furthermore, rectification of the image pair based on the affine fundamental matrix can achieve better performance with much less geometric distortion.

Experimental and numerical studies concerning CNTRCs have shown that distributing CNTs uniformly as the reinforcements in the matrix can achieve moderate improvement of the mechanical properties only (Seidel and Lagoudas 2006).

With the parameters M and N, our new deterministic matrix can achieve the various permissible compression ratios of M N ≈ 1 L for a positive integer L, 2 ≤ L ≤ M-1.

In this context, the number of different scores that the matrix can achieve is significantly larger.

From the figure, it can be concluded that the proposed TDE method with the low-complexity parallel block inverse matrix algorithm can achieve much better BER performance than the conventional FDE methods of using the complexity reduction methods even when employing higher efficient modulation method of 16QAM.

This paper also concluded that the proposed TDE method with the parallel block inverse matrix algorithm can achieve much better BER performance than the conventional FDE methods of using the complexity reduction methods with allowable increase of computation complexity in higher time-varying fading channels.

By using these binary matrices, we can achieve errorless transmission in the absence of noise.

This feature enables to employ the parallel block inverse matrix algorithm which can achieve the same BER performance with much lower computation complexity as compared with that of the direct inverse matrix calculation [15].

This section also proposes the TDE method of using a low-complexity parallel block inverse matrix algorithm which can achieve better BER performance than the conventional FDE methods with keeping lower complexity even in higher time-varying fading channels.

Existing methods, such as memory and Matrix Factorization (MF) approaches can achieve very good recommendation accuracy, unfortunately they are computationally very expensive.